# Project 2: High Resolution Mutation Spectra and Multi-Omics for Deducing Etiology and Predicting Disease

> **NIH NIH P42** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2022 · $520,663

## Abstract

PROJECT SUMMARY/ABSTRACT – PROJECT 2
Exposure of people to single chemicals or mixtures at Superfund sites has unquestionably occurred. The
unanswered question addressed here is whether those exposures can be associated with measurable risks to
genome integrity or expression, which would provide biological plausibility to the argument that the chemicals in
the environment have affected human health and welfare. The compounds chosen for investigation were inspired
by engagement efforts with a local community containing a Superfund site and with Tribal groups in Maine.
Carcinogenic N-nitrosamines (e.g., N-nitrosodimethylamine or NDMA) as well as other toxicants are abundant
in both of our catchment areas. These agents have not been studied as mutagens or proteome disruptors at the
level of detail proposed here, and they certainly have not been subjected to the combined multi-omic scrutiny of
this Project taken together with Project 1 (DNA damage and gene-environment interactions). The technology of
Project 2 has five components: (a) We employ a genetically engineered panel of mice (Project 1) that responds
to environmental toxicants in a manner that reveals underlying mechanisms that confer susceptibility to a
toxicant. The pathway to toxicity involves disease initiation, concomitant complications such as tissue-destructive
inflammation, through end stage pathologies such as cancers. (b) We use a newly developed high-fidelity DNA
sequencing procedure that provides unprecedentedly high-resolution mutational spectra (HRMS); HRMS can be
used to identify chemical-specific mutational patterns resulting from environmental exposures. (c) We use a
unique proteomic platform that sensitively senses disruptions in thousands of nodes in signaling networks. (d)
We use a novel computational module via the Data Management and Analysis Core that quantitatively
compares HRMS and proteomic patterns from our models with the rapidly expanding human data sets of The
Cancer Genome Atlas Project (TCGA), other tumor sequencing efforts, and the growing body of knowledge of
proteomic patterns. (e) Lastly, we introduce mouse embryo fibroblast (MEF) lines isogenic with our mouse
models that can be used as high-throughput screening tools to help find genotoxic fractions in complex mixtures
(Projects 3 and 4). Our multi-omic approach centers on animal and cellular models, but we also look ahead to
application of these novel tools for molecular epidemiology and for disease prevention. Regarding the latter
possibility, the proteomic and mutagenic biomarkers we already see in our work can be immediately be used to
assess the efficacy of probiotic mitigation of disease, via our interactions with Project 1. Regarding contributions
to epidemiology, the distinctive mutational spectra we have already observed following NDMA exposure to
animals and cells could eventually become valuable early-onset biomarkers that portend later life diseases.
Taken together, this Project leverages basic...

## Key facts

- **NIH application ID:** 10351933
- **Project number:** 2P42ES027707-06
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** JOHN M ESSIGMANN
- **Activity code:** P42 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $520,663
- **Award type:** 2
- **Project period:** 2017-09-01 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10351933

## Citation

> US National Institutes of Health, RePORTER application 10351933, Project 2: High Resolution Mutation Spectra and Multi-Omics for Deducing Etiology and Predicting Disease (2P42ES027707-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10351933. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*